Ultrasonic diagnostic apparatus and ultrasonic diagnostic method

ABSTRACT

An ultrasonic diagnostic apparatus ( 100 ) that decides a type of a tumor contained in a specimen includes: an image forming unit ( 103 ) that forms an ultrasonic image corresponding to an echo signal received from the specimen after administration of a contrast medium; a feature value calculating unit ( 106 ) that classifies each of a plurality of pixel regions contained in a tumor region including the tumor in the ultrasonic image into a low-luminance region, or a high-luminance region having higher luminance than the luminance of the low-luminance region, and calculates, based on a difference between a variance at a position of the low-luminance region and a variance at a position of the high-luminance region, a ring level indicating a degree of a ring shape of an image of the tumor region, the ring shape in which a luminance value of a central portion is lower than a luminance value of a peripheral portion surrounding the central portion; and a type deciding unit ( 107 ) that decides the type of the tumor based on the ring level.

CROSS REFERENCE TO RELATED APPLICATION

This Application is a 371 of PCT/JP2013/006113 filed on Oct. 11, 2013which, in turn, claimed the priority of Japanese Patent Application No.JP2012-232041 filed on Oct. 19, 2012, both applications are incorporatedherein by reference.

TECHNICAL FIELD

The present invention relates to an ultrasonic diagnostic apparatus andan ultrasonic diagnostic method. More particularly, the presentinvention relates to an ultrasonic diagnostic apparatus and anultrasonic diagnostic method for deciding a type of a tumor contained ina specimen.

BACKGROUND ART

Ultrasonography is one of image diagnostic methods capable of forminghighly sensitive images of blood vessels by administration of a contrastmedium into the blood vessels. In Japan, the use of a contrast mediumcalled Sonazoid is currently approved for diagnosing liver tumors andmammary tumors. The contrast medium of Sonazoid is employed for decidingtypes of tumors.

In practical situations of diagnosis, an operator initially checks thepresence or absence of a tumor. A tumor is recognized as a hypoechogenicregion or a hyperechogenic region in an ultrasonic image. Then, acontrast medium is administrated, and the tumor is imaged.

At present, a tumor type decision is made based on subjective decisionof a person reading images (operator). This situation causes a problemthat diagnosis results are dependent on the person reading the images.

For overcoming this problem, Patent Literature 1 discloses objectivedifferential diagnostic methods based on time-series changes of twotypes of feature values, i.e., average luminance and standard deviationsexhibited in a tumor region.

According to the technology disclosed in Patent Literature 1, large andsmall three circles containing a tumor are defined, and comparisons aremade between temporal waveforms of the feature values in the respectivecircles and typical waveforms of respective types. Then, the typeproducing the closest waveforms is decided as the type of the tumor.Alternatively, the type producing feature values closest to the featurevalues of the three circles is decided for each time phase. Then, thetype decided the largest number of times is decided as the type of thetumor.

CITATION LIST Patent Literatures

-   Patent Literature 1: JP 2010-005263 A-   Patent Literature 2: U.S. Pat. No. 5,632,277-   Patent Literature 3: U.S. Pat. No. 5,706,819-   Patent Literature 4: U.S. Pat. No. 5,577,505

Non Patent Literature

-   Non Patent Literature 1: Ultrasonic Diagnostic Criteria for Liver    Tumor (Proposal)    http://www.jsum.or.jp/committee/diagnostic/pdf/liver_tumor.pdf

SUMMARY OF INVENTION Technical Problem

According to the foregoing tumor type decision methods, however, highlyaccurate tumor type decision has been demanded.

Accordingly, it is an object of the present invention to provide anultrasonic diagnostic apparatus capable of deciding tumor types withhigh accuracy.

Solution to Problem

In order to achieve the above object, an ultrasonic diagnostic apparatusaccording to an aspect of the present invention is an ultrasonicdiagnostic apparatus that decides a type of a tumor contained in aspecimen, and includes: an image forming unit that forms an ultrasonicimage corresponding to an echo signal received from the specimen afteradministration of a contrast medium; a feature value calculating unitthat classifies each of a plurality of pixel regions contained in atumor region including the tumor in the ultrasonic image into alow-luminance region, or a high-luminance region having higher luminancethan the luminance of the low-luminance region, and calculates, based ona difference between a variance at a position of the low-luminanceregion and a variance at a position of the high-luminance region, a ringlevel indicating a degree of a ring shape of an image of the tumorregion, the ring shape in which a luminance value of a central portionis lower than a luminance value of a peripheral portion surrounding thecentral portion; and a type deciding unit that decides the type of thetumor based on the ring level.

The foregoing general or specific aspects may be realized in the form ofa system, a method, an integrated circuit, a computer program, or arecording medium such as a CD-ROM readable by a computer, or may berealized by arbitrary combinations of a system, a method, an integratedcircuit, a computer program, and a recording medium.

Advantageous Effects of Invention

According to the present invention, there can be provided an ultrasonicdiagnostic apparatus capable of deciding tumor types with high accuracy.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a view illustrating imaging patterns of a liver tumor.

FIG. 2 is a view illustrating a problem.

FIG. 3 is a block diagram illustrating a configuration of an ultrasonicdiagnostic apparatus according to a first embodiment.

FIG. 4 is a flowchart showing operation executed by the ultrasonicdiagnostic apparatus prior to administration of a contrast mediumaccording to the first embodiment.

FIG. 5 is a view illustrating an example of a display screen accordingto the first embodiment.

FIG. 6 is a flowchart showing operation executed by the ultrasonicdiagnostic apparatus after administration of the contrast mediumaccording to the first embodiment.

FIG. 7 is a view illustrating another example of the display screenaccording to the first embodiment.

FIG. 8 is a view illustrating examples of feature values in case of atypical example of a liver tumor.

FIG. 9 is a view illustrating a tumor type deciding process based on thefeature values according to the first embodiment.

FIG. 10 is a view illustrating a further example of the display screenaccording to the first embodiment.

FIG. 11 is a flowchart showing feature value calculating operationaccording to the first embodiment.

FIG. 12A is a view illustrating measurement of a size of a tumoraccording to the first embodiment.

FIG. 12B is a view illustrating size setting of a differential filteraccording to the first embodiment.

FIG. 13A is a view illustrating an example of the differential filterand a shift range of the differential filter according to the firstembodiment.

FIG. 13B is a view illustrating another example of the differentialfilter and the shift range of the differential filter according to thefirst embodiment.

FIG. 13C is a view illustrating a further example of the differentialfilter and the shift range of the differential filter according to thefirst embodiment.

FIG. 14 is a flowchart showing feature value calculating operationaccording to a second embodiment.

FIG. 15 is a view illustrating the feature value calculating operationaccording to the second embodiment.

FIG. 16 is a flowchart showing feature value calculating operationaccording to a third embodiment.

FIG. 17 is a view illustrating the feature value calculating operationaccording to the third embodiment.

FIG. 18 is a flowchart showing feature value calculating operationaccording to a fourth embodiment.

FIG. 19 is a view illustrating the feature value calculating operationaccording to the fourth embodiment.

FIG. 20 is a flowchart showing feature value calculating operationaccording to a fifth embodiment.

FIG. 21 is a view illustrating the feature value calculating operationaccording to the fifth embodiment.

FIG. 22A is a view illustrating an example of a TIC according to thefifth embodiment.

FIG. 22B is a view illustrating an example of the TIC according to thefifth embodiment.

FIG. 23 is a flowchart showing operation executed by the ultrasonicdiagnostic apparatus according to the first embodiment and an ultrasonicdiagnostic apparatus according to the second embodiment.

FIG. 24 is a flowchart showing operation executed by an ultrasonicdiagnostic apparatus according to the third embodiment.

FIG. 25 is a flowchart showing operation executed by ultrasonicdiagnostic apparatuses according to the fourth and fifth embodiment.

DESCRIPTION OF EMBODIMENTS Findings on which the Present Invention isBased

The present inventors have found that the following problems arise fromthe type decision methods described in the section of “Background Art”.

FIG. 1 illustrates a typical example of imaging patterns of a livertumor (Non Patent Literature 1).

There are roughly two types of imaging time phases. One type of theimaging time phases is a vascular phase as a time phase after an elapseof approximately two minutes from administration of a contrast medium,while the other is a post vascular phase as a time phase after an elapseof approximately ten minutes and longer. The vascular phase is a timephase when a time-series change is remarkable in an imaging pattern,while the post vascular phase is a time phase when a time-series changeis small in an imaging pattern. In more detail, the vascular phase isdivided into an artery phase where predominant entrance of blood is froman artery which supplies oxygen to the liver, and a portal phase wherepredominant entrance of blood is from a portal. With a rise ofmalignancy of a tumor, it is considered that the supply of oxygen fromthe artery becomes more predominant along with decrease in the entranceof blood from the portal.

In practical situations of diagnosis, a user observes time-serieschanges of these imaging patterns to decide a tumor type. For example,hepatoma is suspected in case of indications of hyperechogenic for atumor region in comparison with a parenchyma region in the vascularphase, and hypoechogenic for the tumor region in comparison with theparenchyma region in the post vascular phase.

Under the present circumstances, a tumor type decision is made based onsubjective decision of a person reading images (user). In this case,such a problem arises that diagnosis results are dependent on the personreading images.

As illustrated in FIG. 1, useful information for making decision inpractical differentiations includes a difference between a tumor regionand a parenchyma region, and imaging patterns in a tumor region (such asring pattern, center pattern, and iso-pattern).

According to the first method of Patent Literature 1, imaging patternsare decided based on standard deviations. In this case, however, it mayoccur that the standard deviation of the center pattern becomesequivalent to the standard deviation of the ring pattern, in whichcondition accurate decision may be difficult to make.

On the other hand, the second method of Patent Literature 1 evaluatesspatial patterns in three circles to evaluate a pattern in a tumorregion. According to this method, however, the pattern in the tumorregion is determined based on a deviation between a predeterminedpattern and the pattern in the tumor region corresponding to thedecision target. In this case, discrepancy between an input pattern 81and a predetermined pattern 80 increases when the input pattern 81exhibits a high-degree ring pattern as illustrated in FIG. 2, forexample. In this condition, the degree of the pattern may be difficultto accurately evaluate.

Moreover, there is a possibility of disagreement between the center of aring pattern and the center of the tumor region. In this case, thedegree of the ring pattern may be similarly difficult to accuratelyevaluate.

An ultrasonic diagnostic apparatus according to an aspect of the presentinvention is an ultrasonic diagnostic apparatus that decides a type of atumor contained in a specimen, and includes: an image forming unit thatforms an ultrasonic image corresponding to an echo signal received fromthe specimen after administration of a contrast medium; a feature valuecalculating unit that classifies each of a plurality of pixel regionscontained in a tumor region including the tumor in the ultrasonic imageinto a low-luminance region, or a high-luminance region having higherluminance than the luminance of the low-luminance region, andcalculates, based on a difference between a variance at a position ofthe low-luminance region and a variance at a position of thehigh-luminance region, a ring level indicating a degree of a ring shapeof an image of the tumor region, the ring shape in which a luminancevalue of a central portion is lower than a luminance value of aperipheral portion surrounding the central portion; and a type decidingunit that decides the type of the tumor based on the ring level.

The ultrasonic diagnostic apparatus thus constructed can decide thedegree of the ring pattern based on the variance of the high-luminanceregion and the variance of the low-luminance region. In this case, theultrasonic diagnostic apparatus can decide the degree of the ringpattern with high accuracy even when the center of the ring pattern isnot present at the center of the tumor region, for example. Accordingly,the ultrasonic diagnostic apparatus can decide the type of the tumorwith high accuracy.

For example, the feature value calculating unit may set the ring levelto a second value when a difference value obtained by subtracting thevariance at the position of the low-luminance region from the varianceat the position of the high-luminance region is a first value, and setthe ring level to a fourth value larger than the second value when thedifference value is a third value larger than the first value.

For example, the feature value calculating unit may classify each of theregions into the low-luminance region when the luminance value of theregion is smaller than a predetermined threshold, and classify each ofthe regions into the high-luminance region when the luminance value ofthe region is larger than the threshold.

For example, the feature value calculating unit may calculate a numbersequence indicating a time-series change of the luminance value for eachof the regions, classify each of the regions into the low-luminanceregion when a difference between the maximum luminance value and theminimum luminance value in the number sequence is smaller than apredetermined threshold, and classify each of the pixels into thehigh-luminance region when the difference in the number sequence islarger than the threshold.

For example, the feature value calculating unit may further calculate adifference between luminance of a parenchyma region contained in theultrasonic image and not including the tumor, and luminance of the tumorregion, and the type deciding unit may decide the type of the tumorbased on the difference between the luminance of the parenchyma regionand the luminance of the tumor region, and on the ring level.

The ultrasonic diagnostic apparatus thus constructed can decide the typeof the tumor based on the luminance difference between the tumor regionand the parenchyma region in the ultrasonic image as well as the ringlevel. Accordingly, the ultrasonic diagnostic apparatus can decide thetype of the tumor with higher accuracy.

An ultrasonic diagnostic method according to an aspect of the presentinvention is an ultrasonic diagnostic method that decides a type of atumor contained in a specimen, and includes: an image forming step thatforms an ultrasonic image corresponding to an echo signal received fromthe specimen after administration of a contrast medium; a feature valuecalculating step that classifies each of a plurality of pixel regionscontained in a tumor region including the tumor in the ultrasonic imageinto a low-luminance region, or a high-luminance region having higherluminance than the luminance of the low-luminance region, andcalculates, based on a difference between a variance at a position ofthe low-luminance region and a variance at a position of thehigh-luminance region, a ring level indicating a degree of a ring shapeof an image of the tumor region, the ring shape in which a luminancevalue of a central portion is lower than a luminance value of aperipheral portion surrounding the central portion; and a type decidingstep that decides the type of the tumor based on the ring level.

The ultrasonic diagnostic method having this configuration can decidethe degree of the ring pattern based on the variance of thehigh-luminance region and the variance of the low-luminance region. Inthis case, the ultrasonic diagnostic method can decide the degree of thering pattern with high accuracy even when the center of the ring patternis not present at the center of the tumor region, for example.Accordingly, the ultrasonic diagnostic method can decide the type of thetumor with high accuracy.

An ultrasonic diagnostic apparatus according to an aspect of the presentinvention is an ultrasonic diagnostic apparatus that decides a type of atumor contained in a specimen, and includes: an image forming unit thatforms an ultrasonic image corresponding to an echo signal received fromthe specimen after administration of a contrast medium into thespecimen; a region of interest setting unit that searches for a firstregion of interest corresponding to a central portion in a ring shape ina tumor region containing the tumor in the ultrasonic image, the ringshape in which a luminance value of the central portion is lower than aluminance value of a peripheral portion surrounding the central portion;a feature value calculating unit that calculates a difference betweenluminance of the first region of interest and luminance of a secondregion of interest corresponding to the peripheral portion to designatethe difference as a ring level indicating a degree of the ring shape ofan image of the tumor region; and a type deciding unit that decides thetype of the tumor based on the ring level.

The ultrasonic diagnostic apparatus thus constructed can decide thedegree of the ring pattern with high accuracy based on the search forthe low-luminance region within the tumor region even when the center ofthe ring pattern is not present at the center of the tumor region, forexample. Accordingly, the ultrasonic diagnostic apparatus can decide thetype of the tumor with high accuracy.

For example, in a plurality of search regions in a predetermined sizecontained in the tumor region and located at different positions, theregion of interest setting unit may search for the search region where aluminance difference between a first region in a range determinedbeforehand in the search regions and a second region in a rangedetermined beforehand and surrounding the first region becomes themaximum, and may set the first region contained in the search regionwhere the luminance difference becomes the maximum as the first regionof interest.

The ultrasonic diagnostic apparatus thus constructed can appropriatelyset the first region of interest corresponding to the central portion ofthe ring pattern within the tumor region. Accordingly, the ultrasonicdiagnostic apparatus can decide the type of the tumor with highaccuracy.

For example, for the region of interest setting unit, the first regionmay be substantially circular, and the second region may be asubstantially circular region centered at the center of the first regionand corresponding a portion other than the first region.

The ultrasonic diagnostic apparatus thus constructed can set the firstregion of interest regardless of the position or shape of the centralportion of the tumor region. Accordingly, the ultrasonic diagnosticapparatus can decide the type of a liver tumor with high accuracy.

For example, the image forming unit may form ultrasonic images in aplurality of time phases including an artery phase, the region ofinterest setting unit may set the first region of interest in theultrasonic image in the artery phase, and the feature value calculatingunit may calculate the plurality of ring levels in the plurality of timephases based on the set first region of interest, and the type decidingunit may decide the type of the tumor based on the plurality ofcalculated ring levels.

The ultrasonic diagnostic apparatus thus constructed can prevent shiftof the position of the first region of interest for each time phase.Accordingly, the ultrasonic diagnostic apparatus can decide the tumortype with high accuracy.

For example, in a plurality of search regions in a predetermined sizecontained in the tumor region and located at different positions, theregion of interest setting unit may search for the search regionexhibiting the minimum luminance, and may set the search regionexhibiting the minimum luminance as the first region of interest.

The ultrasonic diagnostic apparatus thus constructed can appropriatelyset the first region of interest corresponding to the central portion ofthe ring pattern within the tumor region. Accordingly, the ultrasonicdiagnostic apparatus can decide the type of the tumor with highaccuracy.

An ultrasonic diagnostic method according to an aspect of the presentinvention is an ultrasonic diagnostic method that decides a type of atumor contained in a specimen, and includes: an image forming step thatforms an ultrasonic image corresponding to an echo signal received fromthe specimen after administration of a contrast medium; a region ofinterest setting step that searches for a first region of interestcorresponding to a central portion in a ring shape in a tumor regioncontaining the tumor in the ultrasonic image, the ring shape in which aluminance value of the central portion is lower than a luminance valueof a peripheral portion surrounding the central portion; a feature valuecalculating step that calculates a difference between luminance of thefirst region of interest and luminance of a second region of interestcorresponding to the peripheral portion to designate the difference as aring level indicating a degree of the ring shape of an image of thetumor region; and a type deciding step that decides the type of thetumor based on the ring level.

The ultrasonic diagnostic method having this configuration can decidethe degree of the ring pattern with high accuracy based on the searchfor the low-luminance region within the tumor region even when thecenter of the ring pattern is not present at the center of the tumorregion, for example. Accordingly, the ultrasonic diagnostic method candecide the type of the tumor with high accuracy.

An ultrasonic diagnostic apparatus according to an aspect of the presentinvention is an ultrasonic diagnostic apparatus that decides a type of atumor contained in a specimen, and includes: an image forming unit thatforms an ultrasonic image corresponding to an echo signal received fromthe specimen after administration of a contrast medium; a feature valuecalculating unit that projects luminance values of a plurality of pixelscontained in a tumor region including the tumor in the ultrasonic imagesuch that the luminance values are projected in a horizontal directionand a vertical direction, and calculates, based on degrees of downwardconvexity exhibited in the projected results, a ring level indicating adegree of a ring shape of an image of the tumor region, the ring shapein which a luminance value of the central portion is lower than aluminance value of a peripheral portion surrounding the central portion,the ring level calculated; and a type deciding unit that decides thetype of the tumor based on the ring level.

The ultrasonic diagnostic apparatus thus constructed calculates thedegree of the ring pattern based on the projected results of theluminance values within the tumor region as projected in the horizontaldirection and the vertical direction. In this case, the ultrasonicdiagnostic apparatus can decide the degree of the ring pattern with highaccuracy even when the center of the ring pattern is not present at thecenter of the tumor region, for example. Accordingly, the ultrasonicdiagnostic apparatus can decide the type of the tumor with highaccuracy.

An ultrasonic diagnostic method according to an aspect of the presentinvention is an ultrasonic diagnostic method that decides a type of atumor contained in a specimen, and includes: an image forming step thatforms an ultrasonic image corresponding to an echo signal received fromthe specimen after administration of a contrast medium; a feature valuecalculating step that projects luminance values of a plurality of pixelscontained in a tumor region including the tumor in the ultrasonic imagesuch that the luminance values are projected in a horizontal directionand a vertical direction, and calculates, based on degrees of downwardconvexity exhibited in the projected results, a ring level indicating adegree of a ring shape of an image of the tumor region, the ring shapein which a luminance value of the central portion is lower than aluminance value of a peripheral portion surrounding the central portion,the ring level calculated; and a type deciding step that decides thetype of the tumor based on the ring level.

The ultrasonic diagnostic method having this configuration calculatesthe degree of the ring pattern based on the projected results of theluminance values within the tumor region as projected in the horizontaldirection and the vertical direction. In this case, the ultrasonicdiagnostic method can decide the degree of the ring pattern with highaccuracy even when the center of the ring pattern is not present at thecenter of the tumor region, for example. Accordingly, the ultrasonicdiagnostic method can decide the type of the tumor with high accuracy.

The foregoing general or specific aspects may be realized in the form ofa system, a method, an integrated circuit, a computer program, or arecording medium such as a CD-ROM readable by a computer, or may berealized by arbitrary combinations of a system, a method, an integratedcircuit, a computer program, and a recording medium.

An ultrasonic diagnostic apparatus according to an aspect of the presentinvention is hereinafter described with reference to the drawings.

Each of embodiments discussed hereinbelow illustrates a preferablespecific example of the present invention. Numerical values, shapes,materials, constituent elements, the positions and connection forms ofthe constituent elements, steps, the order of the steps, and others arepresented by way of example only, and not intended to limit the presentinvention. In addition, constituent elements not included in theindependent claims defining the uppermost concepts of the presentinvention are presented as arbitrary constituent elements included inmore preferable modes.

Configuration and operation of a system are now described.

First Embodiment

Discussed in this embodiment is an example which adopts feature valuesreflecting a luminance difference between a tumor region (target region)and a parenchyma region in an ultrasonic image, and imaging patterns(such as ring pattern, center pattern, and iso-pattern) in the tumorregion to decide a type of a liver tumor with high accuracy. The “tumor”in this context refers to a tissue exhibiting properties different fromthose of other tissues, including both a benign tumor and a malignanttumor.

FIG. 3 is a block diagram illustrating a configuration of an ultrasonicdiagnostic apparatus 100 according to this embodiment.

As illustrated in FIG. 3, an ultrasonic system according to thisembodiment includes the ultrasonic diagnostic apparatus 100, anultrasonic probe 101, an input device 110, and a display device 111. Theultrasonic diagnostic apparatus 100 includes an ultrasonic wavetransmitting and receiving unit 102, an image forming unit 103, a datastoring unit 104, a region of interest setting unit 105, a feature valuecalculating unit 106, a type deciding unit 107, a display screencreating unit 108, and an input value acquiring unit 109.

(Configuration)

The ultrasonic probe 101 converts electric signals output from theultrasonic wave transmitting and receiving unit 102 into ultrasonicwaves, and transmits the ultrasonic waves to a specimen. Then, theultrasonic probe 101 receives echo signals reflected on the specimen andreturning to the ultrasonic probe 101, converts the received echosignals into electric signals, and outputs the electric signals to theultrasonic wave transmitting and receiving unit 102.

The ultrasonic wave transmitting and receiving unit 102 generateselectric signals corresponding to original signals of ultrasonicsignals, and outputs the generated electric signals to the ultrasonicprobe 101. In addition, the ultrasonic wave transmitting and receivingunit 102 converts electric signals output from the ultrasonic probe 101into digital echo signals, and outputs the echo signals to the imageforming unit 103.

The image forming unit 103 converts the echo signals output from theultrasonic wave transmitting and receiving unit 102 into luminancevalues to form an ultrasonic image. The image forming unit 103 storesthe formed ultrasonic image in the data storing unit 104.

The data storing unit 104 stores the input image (ultrasonic image),information on a cross section of interest including a tumor,information on regions of interest used for type decision, learning dataused for type decision, feature values of input data used for typedecision, and others.

The input value acquiring unit 109 acquires information on the crosssection of interest, the regions of interest and others designated by anoperator via the input device 110, and stores this information in thedata storing unit 104.

The region of interest setting unit 105 reads an image of the crosssection of interest and the input image from the data storing unit 104,and calculates a positional deviation between these images. Then, theregion of interest setting unit 105 reads information on the regions ofinterest from the data storing unit 104, and corrects the positions ofthe regions of interest in the input image based on the calculatedpositional deviation. Thereafter, the region of interest setting unit105 stores the corrected information on the regions of interest in thedata storing unit 104.

The feature value calculating unit 106 reads the input image and thecorrected information on the regions of interest from the data storingunit 104, and extracts predetermined feature values from the regions ofinterest in the input image. Then, the feature value calculating unit106 arranges the calculated feature values in time series, and storesthe feature values in the data storing unit 104.

The type deciding unit 107 reads, from the data storing unit 104,feature values in the range from administration of a contrast medium toa post vascular phase, and learning data for each type, and then decidesthe tumor type based on the obtained information. The type deciding unit107 having decided the tumor type stores the type decision result in thedata storing unit 104.

The display screen creating unit 108 reads the input image, the featurevalues, the type decision result and others from the data storing unit104 to create a display screen based on the obtained information. Thedisplay screen thus created is displayed on the display device 111.

The input device 110 receives input from the operator. The input device110 is constituted by a trackball, a button, a touch panel or the like.

The display device 111 displays the display screen created by thedisplay screen creating unit 108. The display device 111 is constitutedby a display or the like.

Discussed hereinabove is the apparatus configuration according to thisembodiment.

(Operation)

The flow of operation according to this embodiment is hereinafterdescribed.

Operation executed by the ultrasonic diagnostic apparatus 100 prior toadministration of a contrast medium is discussed at first. FIG. 4 is aflowchart showing operation prior to administration of the contrastmedium according to this embodiment.

[Step S101]

Initially, the image forming unit 103 converts echo signals output fromthe ultrasonic wave transmitting and receiving unit 102 into luminancevalues to form an ultrasonic image. Then, the image forming unit 103stores the ultrasonic image thus formed in the data storing unit 104 asan input image. The display screen creating unit 108 reads the inputimage from the data storing unit 104 where the input image has beenstored by the image forming unit 103. Then, the display screen creatingunit 108 integrates the input image with patient information, settinginformation and others to create a display screen, and displays thecreated display screen on the display device 111. A display mode forthis display is referred to as a normal mode. The normal modecorresponds to a display mode prior to administration of the contrastmedium.

[Step S102]

In step S101, the input value acquiring unit 109 receives operation ofplay stop from the operator. When the operator inputs operation forstopping play through the input device 110, the flow goes to step S103to execute a process in step S103. On the other hand, when the operatordoes not input operation for stopping play, the flow returns to stepS101.

[Step S103]

When it is detected that the operator has input play stop operationthrough the input device 110, the ultrasonic wave transmitting andreceiving unit 102 and the image forming unit 103 stop transmission andreception of ultrasonic waves and image formation, respectively. Then,the display screen creating unit 108 displays a still image on thedisplay device 111. The region of interest setting unit 105 registers anultrasonic image stored in the data storing unit 104 and correspondingto an image in a stop state as a cross section of interest.

[Step S104]

When the operator inputs type decision operation through the inputdevice 110 in a subsequent step, the region of interest setting unit 105detects candidates for a tumor region and a parenchyma region, i.e.,regions of interest, from the cross section of interest, and stores thedetection results in the data storing unit 104 as information on theregions of interest. Then, the display screen creating unit 108 readsinformation on the cross section of interest and the regions of interestfrom the data storing unit 104 where the information has been stored bythe region of interest setting unit 105, creates a display screen whichcontains the information indicating the regions of interest superimposedon the cross section of interest, and displays the created displayscreen on the display device 111. On the display screen, the outer edgesof the regions of interest are displayed in broken lines, for example.Alternatively, the entire regions of interest are colored to such anextent that the image of the cross section of interest can be seenthrough the regions of interest.

FIG. 5 illustrates an example of the display screen in the normal mode.In FIG. 5, an ultrasonic image G11 is displayed on a display screen(normal mode) G10. The ultrasonic image G11 contains a tumor region G12and a parenchyma region G13. The ultrasonic image G11 herein is an inputimage read from the data storing unit 104.

The region of interest setting unit 105 uses a two-dimensionaldifferential filter to detect a candidate for the tumor region. Thecoefficients of the two-dimensional differential filter are sodetermined that a filter value becomes a large value in a region wherethe luminance distribution is low at the center and high in theperiphery, and in a region where the luminance distribution is high atthe center and low in the periphery. The region of interest setting unit105 shifts the two-dimensional differential filter throughout the screento calculate a filter value for each position.

A plurality of candidates in different sizes are detectable for thetumor region by varying the resolution of the input image correspondingto the filtering target. For example, when the resolution of the inputimage is changed to half of the resolution, a tumor in a size twicelarger than the size of the tumor in the foregoing example is detectableby using the differential filter in the same size. Accordingly, aplurality of candidates in different sizes are detectable for the tumorregion by the use of images in several patterns of resolution fordetection of candidates for the tumor region.

The region of interest setting unit 105 having calculated filter valuesfor the respective positions designates, as a candidate for the tumorregion, the region having the maximum filter value in the plurality ofcalculated filter values.

In addition, the region of interest setting unit 105 designates, as acandidate for the parenchyma region, a region located at the same depthas the depth of the detected tumor region. The parenchyma region in thiscontext refers to a normal region not containing a tumor. The parenchymaregion is set to a region in the vicinity of the tumor region.

While the candidate for the tumor region is detected by using thetwo-dimensional differential filter according to the foregoing example,the tumor region may be determined based on reading of the ultrasonicimage by the operator instead of the use of the differential filter.

Each shape of the tumor region and the parenchyma region is a circularor elliptical shape, for example, but is not limited to these shapes.The shapes of the tumor region and the parenchyma region may bearbitrary shapes such as a polygonal shape.

[Step S105]

Then, the display screen creating unit 108 displays, on the displaydevice 111, a confirmation message for confirming whether or not thecandidates for the regions of interest are appropriate.

[Step S106]

Then, the input value acquiring unit 109 receives input from theoperator as a response to the confirmation message in step S105 via theinput device 110. The input from the operator in response to theconfirmation message is completion of setting of the regions ofinterest, or correction for the parenchyma region or the tumor region.

[Step S107]

When the operator inputs completion of setting of the regions ofinterest, the input value acquiring unit 109 makes a final decision onthe information about the regions of interest stored in the data storingunit 104.

[Step S108]

When the operator corrects the tumor region through the input device 110in response to the confirmation message in step S105, the region ofinterest setting unit 105 changes the parenchyma region in accordancewith the correction of the tumor region. Then, the flow goes to stepS109 to execute a process in step S109.

[Step S109]

When the operator corrects the parenchyma region through the inputdevice 110 in response to the confirmation message in step S105, orafter the parenchyma region is changed in step S108, the region ofinterest setting unit 105 corrects the information about the regions ofinterest stored in the data storing unit 104. Then, the flow returns tostep S105, where the display screen creating unit 108 displays aconfirmation message.

Discussed hereinabove is the flowchart showing settings of the crosssection of interest, and regions of interest according to thisembodiment.

Operation executed by the ultrasonic diagnostic apparatus 100 afteradministration of the contrast medium is hereinafter described. FIG. 6is a flowchart showing operation after administration of the contrastmedium according to this embodiment.

[Step S201]

After the final decision is made on the regions of interest in the crosssection of interest in step S107, the ultrasonic wave transmitting andreceiving unit 102 and the image forming unit 103 initially executetransmission and reception of ultrasonic waves corresponding to imagingultrasonic waves, and image formation, respectively. More specifically,the image forming unit 103 forms a contrast image G21 where reflectionecho from the contrast medium is predominant, and a tissue image G22where reflection echo from a tissue is predominant, by using known pulseinversion or amplitude modulation (see Patent Literatures 2, 3, and 4),for example. The tissue image G22 in this context is an imagecorresponding to fundamental wave components of received ultrasonicwaves. Then, the image forming unit 103 stores the contrast image G21and the tissue image G22 in the data storing unit 104. The displayscreen creating unit 108 reads the contrast image G21 and the tissueimage G22 from the data storing unit 104 where the images have beenstored by the image forming unit 103, and creates a display screencontaining these images arranged in the left-right direction.

FIG. 7 illustrates an example of the display screen in an imaging mode.As illustrated in FIG. 7, there are displayed on a display screen G20(imaging mode) the contrast image G21 and the tissue image G22corresponding to ultrasonic images, and a feature value transition G25.The contrast image G21 contains a tumor region G23A and a parenchymaregion G24A. On the other hand, the tissue image G22 contains a tumorregion G23B and a parenchyma region G24B.

The contrast image G21 and the tissue image G22 are the contrast imageG21 and the tissue image G22 read from the data storing unit 104 andarranged in the left-right direction. The tumor regions G23A and G23Band the parenchyma regions G24A and G24B are designated by the system orthe operator. The feature value transition G25 is a time-series displayof feature values used for making type decision.

The display screen creating unit 108 displays the created display imageon the display device 111.

[Step S202]

Then, the region of interest setting unit 105 calculates a positionaldeviation between the cross section of interest and the input imagestored in the data storing unit 104. This positional deviation isproduced by hands movement of the operator, or movements of livingbodies in accordance with the heart movement and breathing. The regionof interest setting unit 105 calculates the deviation based on knownpattern matching. This pattern matching is executed by using the tissueimage G22 formed by the image forming unit 103 in step S201 and lessinfluenced by reflection echo from the contrast medium.

[Step S203]

Then, the region of interest setting unit 105 determines whether or notthe cross section of interest and the input image after positionalcorrection, both of which are stored in the data storing unit 104, areconstituted by the same cross section. For example, the region ofinterest setting unit 105 calculates a discrepancy between both theimages, and determines that both the images are constituted by the samecross section when the discrepancy is a threshold or smaller. When it isdetermined that both the images are constituted by the same crosssection, the region of interest setting unit 105 corrects the positionsof the regions of interest in the input image based on the deviationcalculated in step S202. When it is determined that the images areconstituted by different cross sections, calculation of the featurevalues is not performed.

[Step S204]

Then, the feature value calculating unit 106 calculates a feature valuee and a feature value r used for making type decision based on theregions of interest in the input image stored in the data storing unit104. The specific method for calculating the value e and the value rwill be described later.

FIG. 8 is a view illustrating examples of the feature value e and thefeature value r in case of a typical example of a liver tumor. In FIG.8, the tumor region exhibits hyperechogenic with respect to thesurroundings when the value e is a positive value, and exhibitshypoechogenic with respect to the surroundings when the value e is anegative value. On the other hand, the exhibited pattern is a ringpattern when the value r is a positive value, and is a center patternwhen the value r is a negative value.

As illustrated in (a) in FIG. 8, hepatoma is characteristic in findingsof a uniform pattern (more precisely, basket pattern) in the vascularphase, and hypoechogenic in the post vascular phase. Accordingly, thevalue r in the vascular phase is close to zero, while the value e in thepost vascular phase is negative.

As illustrated in (b) in FIG. 8, metastatic liver cancer ischaracteristic in findings of a ring pattern in the vascular phase andhypoechogenic in the post vascular phase. Accordingly, the value r inthe vascular phase is positive, while the value e in the post vascularphase is negative.

As illustrated in (c) in FIG. 8, hemangioma of liver is characteristicin findings of transition from a ring pattern to a uniform pattern inthe vascular phase and hypoechogenic in the post vascular phase.Accordingly, the value r in the vascular phase changes from a positivevalue to zero, while the value e in the post vascular phase is negative.

As illustrated in (d) in FIG. 8, FNH (focal nodular hyperplasia) ischaracteristic in findings of a cartwheel pattern expanding from thecenter to the outside in the vascular phase and isoechogenic in the postvascular phase. Accordingly, the value r in the vascular phase changesfrom a negative value to zero, while the value e in the post vascularphase is close to zero.

As apparent from these examples, the characteristic findings of a livertumor are supportable by the use of the value e and value r.

[Step S205]

Then, the input value acquiring unit 109 receives operation from theoperator. When the operator inputs a request for ending the operation,the flow goes to step S206 to execute a process in step S206.

[Step S206]

Then, the type deciding unit 107 makes tumor type decision based on thelearning data and the feature values in the range from the vascularphase to the post vascular phase stored in the data storing unit 104.

Feature values 61 for respective fixed sections of interest determinedbeforehand are used for making type decision.

FIG. 9 is a view illustrating tumor type decision based on featurevalues according to this embodiment. Sections T1 to T3 are sections ofinterest 60 used for type decision. Values e1 to e3, and values r1 to r3are average values of values e and values r belonging to the respectivesections of interest 60. According to an example illustrated in FIG. 9,tumor type decision is made based on six input parameters. Discussedherein is a case of type decision using a known support vector machine(linear). Assuming learning data for a type i as w(i) and b (i), anevaluation value as m(i), and an input parameter as x, a relation of(Equation 1) holds.[Equation 1]m(i)={right arrow over (w)}(i)·{right arrow over (x)}−{right arrow over(b)}(i)  Equation (1)

In this case, the values w(i) and b(i) are learning data calculated bythe support vector machine, and prepared for each type i. The details ofthe learning method are not described herein. In case of tumor typedecision to be made for input data, the type deciding unit 107calculates the evaluation value m(i) for all of the types, and decides,as the type of the input data, the type whose evaluation value m becomesthe maximum.

The display screen creating unit 108 may display the decided type. FIG.10 shows a screen display example of the decision results. Asillustrated in this figure, the display screen creating unit 108 maydisplay information indicating a plurality of types corresponding todecision targets, and probabilities of the respective types. The displayscreen creating unit 108 may display this information in a graphicalmanner such as a bar graph, or may display only the type which has thehighest probability.

Calculation of the feature values executed in step S204 is now describedwith reference to FIG. 11. FIG. 11 is a flowchart showing calculation ofthe feature values according to this embodiment.

[Step S301]

Initially, the region of interest setting unit 105 measures the size ofa tumor region 70 (vertical width h and horizontal width w) asillustrated in FIG. 12A.

[Step S302]

Then, the region of interest setting unit 105 determines the size of adifferential filter 72 based on the measured tumor size. Thedifferential filter 72 is provided for detecting a ring pattern. Asillustrated in FIG. 12B, a coefficient 74 at the center of thedifferential filter 72 is negative, while a coefficient 73 in theperiphery is positive. The former region having the negative coefficientcorresponds to a first region of interest in a central portion of thering pattern of the tumor region 70, while the latter region having thepositive coefficient corresponds to a second region of interest in aperipheral portion of the ring pattern of the tumor region 70.

According to the example illustrated in FIG. 12B, the size of thedifferential filter 72 has a length corresponding to the vertical widthof the tumor region 70, i.e., the vertical width smaller than thehorizontal width of the tumor region 70. The shape of the differentialfilter 72 is a square shape. The size of the negative region is half thesize of each of the vertical and horizontal widths of the differentialfilter 72. However, the size of the negative region is not limited tothis size. It is preferable that the size of the negative region liesapproximately in the range from half the size of each of the verticaland horizontal widths of the differential filter 72 to three fourths ofthe size of each of the vertical and horizontal widths of thedifferential filter 72.

[Step S303]

Then, the feature value calculating unit 106 shifts the differentialfilter 72 within the tumor region 70 as illustrated in FIG. 13A, andperforms product-sum operation for the differential filter 72 and theimage at each position to obtain derivatives. More specifically,assuming a pixel value as p, a coefficient value of the differentialfilter 72 as f, and the size (range) of the differential filter 72 as R,a derivative d at a position (x, y) in the image is expressed as thefollowing (Equation 2).[Equation 2]

$\begin{matrix}{{d\left( {x,y} \right)} = {\sum\limits_{i,{j \in R}}^{\;}\;{{p\left( {{x + i},{y + j}} \right)} \cdot {f\left( {i,j} \right)}}}} & {{Equation}\mspace{14mu}(2)}\end{matrix}$

Then, the feature value calculating unit 106 sets the maximum derivatived in the plurality of calculated derivatives d as the value r (featurevalue r) corresponding to an image feature value. More specifically,assuming that a scan range within the tumor region 70 is S, the value ris expressed as the following (Equation 3).[Equation 3]

$\begin{matrix}{r = {\underset{x,{y \in S}}{MAX}\left\lbrack {d\left( {x,y} \right)} \right\rbrack}} & {{Equation}\mspace{14mu}(3)}\end{matrix}$

By this method, the feature value calculating unit 106 can extract thefeature value at the position where the ring pattern is most prominentwithin the tumor region 70.

[Step S304]

Finally, the feature value calculating unit 106 calculates an averageluminance value for each of the tumor region 70 and parenchyma region,and sets the difference between these average values as the value e(feature value e) corresponding to an image feature value. In this case,the feature value calculating unit 106 may calculate, as the averageluminance value of the tumor region 70, an average luminance value inthe image region where the maximum feature value d is calculated (in thesame size as the size R of the differential filter 72), or an averageluminance value of the entire tumor region detected or set in step S104.

Assuming the average luminance of the tumor region 70 as x, and theaverage luminance of the parenchyma region as y, the value e isexpressed by the following (Equation 4).[Equation 4]e=x−y  Equation (4)

The feature value calculating unit 106 may set the size of thedifferential filter 72 to a further smaller size than the smaller widthof either the vertical width or horizontal width of the tumor region 70so as to conduct finer scanning for the inside of the tumor region 70 asillustrated in FIG. 13B. In addition, the shape of the differentialfilter 72 may be a circular shape or an approximately circular shape asillustrated in FIG. 13C.

The feature value calculating unit 106 may scan the differential filter72 only when the luminance of the tumor region 70 becomes apredetermined threshold or higher. This method initiates scanning priorto the time of contrast, wherefore the detection results do not becomeinstable.

The feature value calculating unit 106 may conduct this scanning onlyfor a predetermined time phase (such as artery phase), and apply theposition of the differential filter 72 determined in the predeterminedtime phase to the following time phases, for example. This methodprevents shift of the determined position of the differential filter 72in the subsequent time phases.

According to the foregoing example, the value r is the differencebetween the luminance value in the peripheral portion where the positivecoefficients of the differential filter 72 are integrated, and theluminance value at the central portion where the negative coefficientsof the differential filter 72 are integrated. However, the value r maybe a luminance difference between the luminance value in the centralportion, and the luminance value in a region contained in the tumorregion 70 and corresponding to a portion other than the central portion.

The display screen creating unit 108 may display the position where thederivative d becomes the maximum. For example, the display screencreating unit 108 draws a substantially circular shape to indicate theouter edge of the central portion, i.e., the boundary between thecentral portion where the negative regions of the differential filter 72are integrated, and the peripheral portion where the positive regions ofthe differential filter 72 are integrated. The display screen creatingunit 108 may also draw a substantially circular shape to indicate theouter edge of the peripheral portion. This method allows the operator torecognize which position in the tumor region has been extracted as thecentral portion of the ring pattern. The display screen creating unit108 may display the central portion and the peripheral portion only whenthe value r is larger than a predetermined threshold. This method allowsthe operator to recognize the situations in deciding likelihood of thering pattern.

The display screen creating unit 108 may display the position of thedifferential filter 72 during scanning in step S303. In addition,buttons or bars for play, pause and the like may be equipped. Moreover,the operator may shift or fix the position of the differential filter72, or modify the shape of the differential filter 72 by dragging themouse on the outer edge of the central portion or the peripheralportion. Particularly, during offline operation of the ultrasonicdiagnostic apparatus 100, correction of the position of the differentialfilter 72 increases the accuracy of the features of the tumor region 70obtained based on observation and experiences of the operator. As aresult, the accuracy of the type decision results improves.

Discussed hereinabove is the flowchart of the operation executed afteradministration of the contrast medium according to this embodiment.

According to the description hereinabove, the candidate for theparenchyma region is set to a region located at the same depth as thedepth of the tumor region and close to the tumor region. However, thecandidate for the parenchyma is not limited to this region. For example,such a region may be selected which has a depth different from the depthof the tumor region when there exists a hyperechogenic region such asthe diaphragm in the region located at the same depth as the depth ofthe tumor region and close to the tumor region.

In calculating the luminance difference between the tumor region and theparenchyma region, the feature value calculating unit 106 is notrequired to calculate the luminance value of the tumor region based onthe luminance value of the entire tumor region, but may calculate theluminance value of the tumor region based on the luminance value of ahypoechogenic region 71 used for calculation of the feature values ofthe ring pattern, for example.

According to the above description, the feature value calculating unit106 uses the average luminance of each of the regions for calculation ofthe feature values. However, other information on luminance may be usedfor this purpose. Other information on luminance in this context mayinclude luminance at a point of a predetermined position within theregion, the center value of luminance of the region, or a mode ofluminance in the region, for example.

The type deciding unit 107 may vary the sections of interest 60 for eachtype of tumors when associating feature values with tumor types.

According to the foregoing example, the type deciding unit 107 uses thesupport vector machine when associating feature values with tumor types.However, the type deciding unit 107 is not required to use the supportvector machine but may adopt other types of machine learning.

Advantageous Effects

As described above, the ultrasonic diagnostic apparatus according to anaspect of the present invention can decide a tumor type based on aluminance difference between two regions of interest contained in atarget region (tumor region) in an ultrasonic image and exhibitingremarkable features for each type of the tumor. More specifically, theultrasonic diagnostic apparatus decides a ring pattern based on theluminance difference between the two regions of interest, and therebyevaluates the degree of the ring pattern. In this case, the ultrasonicdiagnostic apparatus more appropriately identifies a tumor type.Accordingly, the ultrasonic diagnostic apparatus can decide a type of aliver tumor with high accuracy without depending on a person who readsimages.

The ultrasonic diagnostic apparatus searches for a region where thedegree of the ring pattern becomes the maximum within a tumor region.Accordingly, the ultrasonic diagnostic apparatus can appropriatelycalculate the degree of the ring pattern even when the ring pattern isnot present at the center of the tumor region.

The ultrasonic diagnostic apparatus decides a tumor type based on theluminance difference between a tumor region and a parenchyma region inan ultrasonic image, as well as on the luminance of the tumor region.Accordingly, the ultrasonic diagnostic apparatus can decide a type of aliver tumor with high accuracy.

The ultrasonic diagnostic apparatus recognizes a tumor region in anultrasonic image as a circular shape, and sets a region of interest foreach of the central portion the circular shape and the peripheralportion of the circular shape. Then, the ultrasonic diagnostic apparatuscalculates the luminance difference between these regions of interest toidentify the type of the tumor based on the luminance difference.Accordingly, the ultrasonic diagnostic apparatus can decide a type of aliver tumor with higher accuracy.

The search for the ring pattern may be limited to the artery phase. Morespecifically, the region of interest setting unit 105 sets the firstregion of interest in an ultrasonic image in the artery phase. Thefeature value calculating unit 106 calculates a ring level (featurevalue r) for each of a plurality of time phases based on the set firstregion of interest. The ring level in this context refers to the degreeof the ring pattern. The type deciding unit 107 decides a tumor typebased on the plurality of calculated ring levels. Accordingly, theultrasonic diagnostic apparatus can prevent shift of the evaluationposition in the ring pattern for each time phase, thereby deciding atype of a liver tumor with high accuracy.

The ultrasonic diagnostic apparatus displays the positions of regions ofinterest in an image, i.e., positions to which the differential filter72 is applied for calculation of the feature value r of the ringpattern. Accordingly, the operator can recognize validity of typedecision.

Second Embodiment

According to the first embodiment discussed above, the feature valuecalculating unit 106 searches for a region where the derivative becomesthe maximum. However, the feature value calculating unit 106 in thisembodiment searches for a region where a luminance value becomes theminimum.

FIG. 14 is a flowchart showing a feature value calculating processaccording to this embodiment.

As illustrated in FIG. 14, the feature value calculating unit 106searches for a region where a luminance value becomes the minimum withina tumor region (S311). More specifically, the feature value calculatingunit 106 scans a search region 75 in the tumor region 70 to search for aregion where the luminance value becomes the minimum as illustrated inFIG. 5. The luminance value in this context refers to an average ofluminance values within the search region 75, for example. The luminancevalue may be a center value or a mode of the luminance values in thesearch region 75, for example. The size of the search region 75 isapproximately equivalent to the size of the region corresponding to thecoefficient 74 at the center of the differential filter 72, for example.

Then, the feature value calculating unit 106 calculates the luminancedifference between the luminance value of the region where the luminancevalue becomes the minimum, and the luminance value of a region containedin the tumor region 70 and corresponding to a portion other than theregion where the luminance value becomes the minimum, and sets thecalculated luminance difference to the feature value r (S312).

As discussed above, the ultrasonic diagnostic apparatus according tothis embodiment searches for the region where the luminance valuebecomes the minimum within the tumor region. Accordingly, the ultrasonicdiagnostic apparatus can appropriately calculate the degree of a ringpattern even when the ring pattern is not present at the center of thetumor region.

Third Embodiment

Discussed in this embodiment is a modified example of the method forcalculating the feature value r.

FIG. 16 is a flowchart showing a feature value calculating processaccording to this embodiment.

Initially, the feature value calculating unit 106 projects a luminancevalue of the tumor region 70 in the vertical direction and thehorizontal direction as illustrated in FIG. 17 (S321). Projecting aluminance value in the vertical direction in this context refers to aprocess for calculating an average of luminance values of a plurality ofpixels contained in pixel columns for each of the pixel columns in thetumor region 70. Similarly, projecting a luminance value in thehorizontal direction in this context refers to a process for calculatingan average of luminance values of a plurality of pixels contained inpixel rows for each of the pixel rows in the tumor region 70. Thisprocess may be executed for each pixel, or may be executed for eachregion containing a plurality of pixels. Alternatively, a center valueor an aspect may be used in place of the average value.

Then, the feature value calculating unit 106 calculates the featurevalue r based on a projection value in the vertical direction and aprojection value in the horizontal direction (S322). More specifically,the feature value calculating unit 106 obtains a degree of downwardconvexity for each of the projection value in the vertical direction andthe projection value in the horizontal direction, and sets therespective degrees of downward convexity as feature values. For example,the feature value calculating unit 106 fits each of the projectionvalues to a function convex downward (such as quadratic function). Morespecifically, the feature value calculating unit 106 determines aquadratic function most fitted to the projection values for each whilevarying coefficient value of the quadratic function. Then, the featurevalue calculating unit 106 sets the coefficient value of the x-squaredterm of the determined quadratic function to the feature value r. Inthis case, the feature value r increases (the degree of the ring shapeincreases) as the degree of the downward convexity of the projectionvalue increases.

As discussed above, the ultrasonic diagnostic apparatus according tothis embodiment decides the degree of the ring pattern based on theprojection values of the luminance values in the tumor region.Accordingly, the ultrasonic diagnostic apparatus can appropriatelycalculate the degree of the ring pattern even when the ring pattern isnot present at the center of the tumor region.

Fourth Embodiment

Discussed in this embodiment is a modified example of the method forcalculating the feature value r.

FIG. 18 is a flowchart showing a feature value calculating processaccording to this embodiment.

Initially, the feature value calculating unit 106 divides the tumorregion 70 into a plurality of small regions 91 as illustrated in FIG. 19(S331). Each of the small regions 91 herein contains a plurality ofpixels. Each of the small regions 91 may contain only one pixel. Inother words, the following process may be executed for each pixelwithout performing this region dividing process.

Then, the feature value calculating unit 106 classifies each of thesmall regions into a high-luminance region 92 or a low-luminance region93 (S332). The high-luminance region 92 in this context refers to aregion having a luminance value (such as average value, center value,and mode) higher than each luminance value of the low-luminance region93. For example, discriminant analysis method or K-means (K-means) maybe adopted for this classification.

Then, the feature value calculating unit 106 calculates a variance Vh atthe positions of the high-luminance regions 92, and a variance V1 at thepositions of the low-luminance regions 93 (S333). More specifically, thevariance Vh is a value calculated by dividing the sum of squares of thedifferences between the average coordinates (center coordinates) at thepositions of the plurality of high-luminance regions 92 and therespective high-luminance regions 92 by the total number of thehigh-luminance regions 92. Similarly, the variance Vl is a valuecalculated by dividing the sum of squares of the differences between theaverage coordinates (center coordinates) at the positions of theplurality of low-luminance regions 93 and the respective low-luminanceregions 93 by the total number of the low-luminance regions 93.

Then, the feature value calculating unit 106 sets the difference betweenthe variance Vh and the variance Vl to the ring level (feature value r)(S334). More specifically, the feature value r is expressed as Vh−Vl. Inother words, the feature value r (ring level) becomes a large value atthe time of a small value of the variance Vl for the low-luminanceregions and a large value of the variance Vh for the high-luminanceregions 92.

As described above, the ultrasonic diagnostic apparatus according tothis embodiment decides the degree of the ring pattern based on thevariances of the high-luminance regions and the low-luminance regions.Accordingly, the degree of the ring pattern can be appropriatelycalculated even when the ring pattern is not present at the center ofthe tumor region.

Fifth Embodiment

Discussed in this embodiment is a modified example of the method forcalculating the feature value r.

FIG. 20 is a flowchart showing a feature value calculating processaccording to this embodiment.

Initially, the feature value calculating unit 106 divides the tumorregion 70 into the plurality of small regions 91 as illustrated in FIG.21 (S341). This process is similar to the process in S331 shown in FIG.18.

Then, the feature value calculating unit 106 creates a TIC (TimeIntensity Curve) for each of the small regions 91 (S342). Each of theTICs herein shows a change of the luminance value with time asillustrated in FIGS. 22A and 22B.

Then, the feature value calculating unit 106 classifies each of thesmall regions 91 into a high-luminance region 94 or a low-luminanceregion 95 (S343) based on the change amount of the TIC. The changeamount in this context refers to a difference between the maximumluminance value and the minimum luminance value in the TIC. The featurevalue calculating unit 106 classifies the target small region 91 intothe high-luminance region 94 when the change amount of the region islarger than a predetermined threshold, and classifies the target smallregion 91 into the low-luminance region 95 when the change amount of theregion is smaller than the predetermined threshold.

Then, the feature value calculating unit 106 calculates the variance Vhat the positions of the high-luminance regions 94, and the variance V1at the positions of the low-luminance regions 95 (S344).

Then, the feature value calculating unit 106 sets the difference betweenthe variance Vh and the variance V1 to the ring level (feature value r)(S345). More specifically, the feature value r is expressed as Vh−Vl. Inother words, the feature value r (ring level) becomes a large value atthe time of a small value of the variance V1 for the low-luminanceregions and a large value of the variance Vh for the high-luminanceregions.

As described above, the ultrasonic diagnostic apparatus according tothis embodiment decides the degree of the ring pattern based on thevariances of the high-luminance regions and the low-luminance regions.Accordingly, the degree of the ring pattern can be appropriatelycalculated even when the ring pattern is not present at the center ofthe tumor region.

CONCLUSION

As described in the first embodiment and the second embodiment, theultrasonic diagnostic apparatus according to an aspect of the presentinvention executes a process shown in FIG. 23. Initially, the imageforming unit 103 forms an ultrasonic image corresponding to echo signalsreceived from a specimen after administration of a contrast medium(S401).

Then, the region of interest setting unit 105 searches for the firstregion of interest from the inside of a tumor region containing a tumorin the ultrasonic image. The first region of interest corresponds to acenter portion having a lower luminance value in a ring shape than theluminance value of a peripheral portion surrounding the central portion(S402).

More specifically, as discussed in the first embodiment, the region ofinterest setting unit 105 searches for a first region and a secondregion where the luminance difference becomes the maximum. In moredetail, the region of interest setting unit 105 searches for a searchregion where the luminance difference between the first region and thesecond region becomes the maximum in a plurality of search regions in apredetermined size contained in the tumor region and located atdifferent positions. Then, the region of interest setting unit 105 setsthe first region contained in the search region exhibiting the maximumluminance difference to the first region of interest. In this case, thefirst region is a range determined beforehand in the search region(differential filter 72), and corresponds to the region of thecoefficient 74 at the center of the differential filter 72. On the otherhand, the second region is a range determined beforehand in the searchregion and surrounding the first region, and corresponds to the regionof the coefficient 73 in the periphery of the differential filter 72.

The first region may be substantially circular, while the second regionmay be a substantially circular region centered at the center of thefirst region and corresponding to a portion other than the first region.

As discussed in the second embodiment, the region of interest settingunit 105 may search for a region where the luminance becomes theminimum. More specifically, the region of interest setting unit 105 maysearch for a search region exhibiting the minimum luminance in theplurality of search regions in a predetermined size contained in thetumor region and located at different positions, and sets the searchregion exhibiting the minimum luminance to the first region of interest.

Then, the feature value calculating unit 106 calculates the differencebetween the luminance of the first region of interest and the luminanceof the second region of interest corresponding to a peripheral portionto designate the difference as a ring level (feature value r) indicatingthe degree of a ring shape in the image of the tumor region (S403). Inthis case, the second region of interest is a portion of the tumorregion other than the first region of interest. As discussed in thefirst embodiment, the second region of interest may be constituted bythe second region when the search is conducted based on the luminancedifference between the first region and the second region.

Then, the type deciding unit 107 decides the tumor type based on thering level (S404).

The foregoing search process (S402) may be executed for each of theplurality of ultrasonic images, or may be executed for only a part ofthe ultrasonic images. When the search process is executed for only apart of the ultrasonic images, the first region of interest searched inthe search process is applied to the other ultrasonic images. Forexample, the image forming unit 103 forms ultrasonic images for aplurality of time phases including an artery phase. The region ofinterest setting unit 105 sets the first region of interest in theultrasonic image for the artery phase. The feature value calculatingunit 106 calculates a plurality of ring levels for the plurality of timephases based on the set first region of interest. The type deciding unit107 decides the tumor type based on the plurality of calculated ringlevels.

As discussed in the third embodiment, the ultrasonic diagnosticapparatus according to an aspect of the present invention executes aprocess shown in FIG. 24. Initially, the image forming unit 103 forms anultrasonic image corresponding to echo signals received from a specimenafter administration of a contrast medium (S411).

Then, the feature value calculating unit 106 projects a plurality ofpixel luminance values contained in a tumor region including a tumor inthe ultrasonic image such that the pixel luminance values are projectedin the horizontal direction and the vertical direction (S412). Then, thefeature value calculating unit 106 calculates a ring level (featurevalue r) indicating the degree of a ring shape based on the degrees ofdownward convexity exhibited in each of the projected results, as such aring shape where the luminance value in the central portion becomeslower than the luminance value in the peripheral portion in the image ofthe tumor region (S413).

Then, the type deciding unit 107 decides the tumor type based on thering level (S414).

As discussed in the fourth embodiment and the fifth embodiment, theultrasonic diagnostic apparatus according to an aspect of the presentinvention executes a process shown in FIG. 25. Initially, the imageforming unit 103 forms an ultrasonic image corresponding to echo signalsreceived from a specimen after administration of a contrast medium(S421).

Then, the feature value calculating unit 106 classifies each of aplurality of pixel regions contained in a tumor region including a tumorin the ultrasonic image into a low-luminance region, or a high-luminanceregion exhibiting higher luminance than in the low-luminance region(S422).

More specifically, as discussed in the fourth embodiment, the featurevalue calculating unit 106 classifies each of the plurality of regionscontained in the tumor region into a low-luminance region when theluminance value of the region (such as average value) is smaller than apredetermined threshold, and classifies each of the regions into ahigh-luminance region when the luminance value of the region is largerthan the predetermined threshold.

Alternatively, as discussed in the fifth embodiment, the feature valuecalculating unit 106 calculates a number sequence (TIC), which indicatesa time-series change of the luminance value in the region, for each ofthe plurality of regions contained in the tumor region. Then, thefeature value calculating unit 106 classifies each of the region intothe low-luminance region when the difference between the maximumluminance value and the minimum luminance value in the number sequenceis smaller than a predetermined threshold, and classifies each of theregion into the high-luminance region when the difference between themaximum luminance value and the minimum luminance value in the numbersequence is larger than the predetermined threshold.

The region in this context is a region containing at least one pixel.

Then, the feature value calculating unit 106 calculates a ring level(feature value r), which level indicates the degree of a ring shapewhere the luminance in the central portion becomes lower than theluminance value in the peripheral portion surrounding the centralportion in the image of the tumor region, as a level calculated based onthe difference between a variance at the position of the low-luminanceregion (variance at the position of at least one region classified intothe low-luminance region) and a variance at the position of thehigh-luminance region (variance at the position of at least one regionclassified into the high-luminance region) (S423). More specifically,the feature value calculating unit 106 sets the ring level to a secondvalue when the difference value obtained by subtracting the variance atthe position of the low-luminance region from the variance at theposition of the high-luminance region is a first value. On the otherhand, the feature value calculating unit 106 sets the ring level to afourth value larger than the second value when the difference value is athird value larger than the first value. In other words, the featurevalue calculating unit 106 sets a larger ring level when the differencevalue is large.

Then, the type deciding unit 107 decides the tumor type based on thering level (S424).

The feature value calculating unit 106 may calculate the difference(feature value e) between the luminance of the tumor region and theluminance of a parenchyma region contained in the ultrasonic image andnot including the tumor, and the type deciding unit 107 decides thetumor type based on the difference between the luminance of the tumorregion and the luminance of the parenchyma region, and on the ringlevel.

Other Modified Examples

While exemplary embodiments according to the present invention have beendescribed, it is obvious that the present invention is not limited tothese embodiments. The following configurations are also included in thescope of the present invention.

(1) Specifically, each of the apparatuses described hereinabove isconstituted by a computer system including a microprocessor, a ROM, aRAM, a hard disk unit, a display unit, a keyboard, a mouse and others.The RAM or the hard disk unit stores a computer program. The functionsof each apparatus are performed in accordance with operation of themicroprocessor under the computer program. The computer program in thiscontext refers to a program constituted by a combination of a pluralityof instruction codes indicating instructions issued to the computer toallow performance of predetermined functions.

(2) Apart or the whole of the constituent elements of each of theapparatuses may be constituted by a single system LSI (Large ScaleIntegration). The system LSI is a super multifunction LSI manufacturedfrom a plurality of constituent units integrated on one chip. Morespecifically, the system LSI is a computer system including amicroprocessor, a ROM, a RAM and others. The RAM stores a computerprogram. The functions of the system LSI are performed in accordancewith operation of the microprocessor under the computer program.

(3) A part or the whole of the constituent elements of each of theapparatuses may be constituted by an IC card or a single moduledetachably attached to each of the apparatuses. The IC card or themodule is a computer system constituted by a microprocessor, a ROM, aRAM and others. The IC card or the module may include the foregoingsuper multifunction LSI. The functions of the IC card or the module areperformed in accordance with operation of the microprocessor under acomputer program. The IC card or the module may have tamper resistance.

(4) The present invention may be practiced as a method for realizing therespective steps described herein. In addition, the present inventionmay be practiced in the form of a computer program executing these stepsby the use of a computer, or in the form of digital signals under thecomputer program.

The present invention may be practiced in the form of a recording mediumrecording the computer program or the digital signals in a mannerreadable by a computer, such a recording medium as a flexible disk, ahard disk, a CD-ROM, an MO, a DVD, a DVD-ROM, a DVD-RAM, a BD (Blu-ray(registered trademark) Disc), and a semiconductor memory. In addition,the present invention may be practiced in the form of the digitalsignals recorded on any one of these recording media.

The present invention may be practiced in the form of the computerprogram or the digital signals transmitted via an electric communicationline, a wireless or wired communication line, a network including theInternet as a typical example, data broadcasting or others.

The present invention may be practiced in the form of a computer systemincluding a microprocessor and a memory. The memory stores the computerprogram, while the microprocessor operates under the computer program.

The present invention may be practiced by another independent computersystem which receives the program or the digital signals transferred inthe form of the recording medium recording the program or the digitalsignals, or transferred via the network.

(5) The respective embodiments and modified examples may be combined.

The respective constituent elements included in the respectiveembodiments may be constituted by dedicated hardware, or realized byexecution of software programs appropriate for the respectiveconstituent elements. The respective constituent elements may berealized by a program executing unit such as a CPU or a processor whichreads and executes a software program recorded in a recording mediumsuch as a hard disk and a semiconductor memory. In this case, thesoftware realizing the ultrasonic diagnostic apparatuses and othersaccording to the respective embodiments is the following program.

The program is a program for causing a computer executes an ultrasonicdiagnostic method that decides a type of a tumor contained in aspecimen, and includes: an image forming step that forms an ultrasonicimage corresponding to an echo signal received from the specimen afteradministration of a contrast medium; a feature value calculating stepthat classifies each of a plurality of pixel regions contained in atumor region including the tumor in the ultrasonic image into alow-luminance region, or a high-luminance region having higher luminancethan the luminance of the low-luminance region, and calculates, based ona difference between a variance at a position of the low-luminanceregion and a variance at a position of the high-luminance region, a ringlevel indicating a degree of a ring shape of an image of the tumorregion, the ring shape in which a luminance value of a central portionis lower than a luminance value of a peripheral portion surrounding thecentral portion; and a type deciding step that decides the type of thetumor based on the ring level.

A program according to an aspect of the present invention is a programfor causing a computer to execute an ultrasonic diagnostic method thatdecides a type of a tumor contained in a specimen, and includes: animage forming step that forms an ultrasonic image corresponding to anecho signal received from the specimen after administration of acontrast medium; a region of interest setting step that searches for afirst region of interest corresponding to a central portion in a ringshape in a tumor region containing the tumor in the ultrasonic image,the ring shape in which a luminance value of the central portion islower than a luminance value of a peripheral portion surrounding thecentral portion; a feature value calculating step that calculates adifference between luminance of the first region of interest andluminance of a second region of interest corresponding to the peripheralportion to designate the difference as a ring level indicating a degreeof the ring shape of an image of the tumor region; and a type decidingstep that decides the type of the tumor based on the ring level.

A program according to an aspect of the present invention is a programfor causing a computer to execute an ultrasonic diagnostic method thatdecides a type of a tumor contained in a specimen, and includes: animage forming step that forms an ultrasonic image corresponding to anecho signal received from the specimen after administration of acontrast medium; a feature value calculating step that projectsluminance values of a plurality of pixels contained in a tumor regionincluding the tumor in the ultrasonic image such that the luminancevalues are projected in a horizontal direction and a vertical direction,and calculates, based on degrees of downward convexity exhibited in theprojected results, a ring level indicating a degree of a ring shape ofan image of the tumor region, the ring shape in which a luminance valueof the central portion is lower than a luminance value of a peripheralportion surrounding the central portion, the ring level calculated; anda type deciding step that decides the type of the tumor based on thering level.

The numerals shown in the above description are all presented only fordescribing specific examples of the present invention, and not forlimiting the scope of the present invention.

Division of function blocks illustrated in the block diagrams ispresented by way of example only. A single function block may beprovided in place of a plurality of function blocks, or a singlefunction block may be divided into a plurality of blocks. Moreover, apart of functions of certain function block or blocks may be shifted todifferent function block or blocks. In addition, functions of aplurality of function blocks having similar functions may be processedin parallel or in a time-sharing manner by single hardware or software.

The order of execution of a plurality of steps included in theultrasonic diagnostic method performed by the ultrasonic diagnosticapparatus is presented only for describing a specific example of thepresent invention, and therefore may be an order different from theorder described herein. In addition, a part of the steps may be executedsimultaneously (in parallel) with other steps.

While the ultrasonic diagnostic apparatus according to one or aplurality of aspects of the present invention has been described basedon exemplary embodiments, the present invention is not limited to theseexemplary embodiments. Modes containing various modifications which maybe made by those skilled in the art, and modes constituted bycombinations of constituent elements in different embodiments may beincluded in the scope of one or a plurality of aspects of the presentinvention without departing from the scope of the present invention.

INDUSTRIAL APPLICABILITY

The present invention is applicable to an ultrasonic diagnosticapparatus. The present invention is also applicable to an ultrasonicdiagnostic method.

REFERENCE SIGNS LIST

-   60 section of interest-   61 feature value-   70 tumor region-   71 hypoechogenic region-   72 differential filter-   73 coefficient of periphery-   74 coefficient of center-   75 search region-   80 predetermined pattern-   81 input pattern-   91 small region-   92, 94 high-luminance region-   93, 95 low-luminance region-   100 ultrasonic diagnostic apparatus-   101 ultrasonic probe-   102 ultrasonic wave transmitting and receiving unit-   103 image forming unit-   104 data storing unit-   105 region of interest setting unit-   106 feature value calculating unit-   107 type deciding unit-   108 display screen creating unit-   109 input value acquiring unit-   110 input device-   111 display device-   G10, G20 display screen-   G11 ultrasonic image-   G12, G23A, G23B tumor region-   G13, G24A, G24B parenchyma region-   G21 contrast image-   G22 tissue image-   G25 feature value transition

The invention claimed is:
 1. An ultrasonic diagnostic apparatus thatdecides a type of a tumor contained in a specimen, the apparatuscomprising: an image forming unit that forms an ultrasonic imagecorresponding to an echo signal received from the specimen afteradministration of a contrast medium; a feature value calculating unitthat classifies each of a plurality of pixel regions contained in atumor region including the tumor in the ultrasonic image into alow-luminance region, or a high-luminance region having higher luminancethan the luminance of the low-luminance region, and calculates, based ona difference between a variance at a position of the low-luminanceregion and a variance at a position of the high-luminance region, a ringlevel indicating a degree of a ring shape of an image of the tumorregion, the ring shape in which a luminance value of a central portionis lower than a luminance value of a peripheral portion surrounding thecentral portion; and a type deciding unit that decides the type of thetumor based on the ring level.
 2. The ultrasonic diagnostic apparatusaccording to claim 1, wherein the feature value calculating unit setsthe ring level to a second value when a difference value obtained bysubtracting the variance at the position of the low-luminance regionfrom the variance at the position of the high-luminance region is afirst value, and sets the ring level to a fourth value larger than thesecond value when the difference value is a third value larger than thefirst value.
 3. The ultrasonic diagnostic apparatus according to claim1, wherein the feature value calculating unit classifies each of theregions into the low-luminance region when the luminance value of theregion is smaller than a predetermined threshold, and classifies each ofthe regions into the high-luminance region when the luminance value ofthe region is larger than the threshold.
 4. The ultrasonic diagnosticapparatus according to claim 1, wherein the feature value calculatingunit calculates a number sequence indicating a time-series change of theluminance value for each of the regions, classifies each of the regionsinto the low-luminance region when a difference between the maximumluminance value and the minimum luminance value in the number sequenceis smaller than a predetermined threshold, and classifies each of thepixels into the high-luminance region when the difference is larger thanthe threshold.
 5. The ultrasonic diagnostic apparatus according to claim1, wherein the feature value calculating unit further calculates adifference between luminance of a parenchyma region contained in theultrasonic image and not including the tumor, and luminance of the tumorregion, and the type deciding unit decides the type of the tumor basedon the difference between the luminance of the parenchyma region and theluminance of the tumor region, and on the ring level.
 6. An ultrasonicdiagnostic method that decides a type of a tumor contained in aspecimen, the method comprising: an image forming step that forms anultrasonic image corresponding to an echo signal received from thespecimen after administration of a contrast medium; a feature valuecalculating step that classifies each of a plurality of pixel regionscontained in a tumor region including the tumor in the ultrasonic imageinto a low-luminance region, or a high-luminance region having higherluminance than the luminance of the low-luminance region, andcalculates, based on a difference between a variance at a position ofthe low-luminance region and a variance at a position of thehigh-luminance region, a ring level indicating a degree of a ring shapeof an image of the tumor region, the ring shape in which a luminancevalue of a central portion is lower than a luminance value of aperipheral portion surrounding the central portion; and a type decidingstep that decides the type of the tumor based on the ring level.
 7. Aprogram stored on a non-transitory medium for causing a computer toexecute the ultrasonic diagnostic method according to claim 6.